There is a famous quote in gambling circles, "if you bet the Super Bowl, you are a losing player". Most, if not all, regular gamblers probably believe they have some system that allows them to beat the bookies. [*] In reality, close to none of them do. That's because the bookmakers have pretty good models that make them fairly accurate at predicting the odds of various outcomes (if they didn't, then they wouldn't remain profitable bookies for long!).
So, the sports odds we observe in the real world pretty accurately reflect the underlying probabilities (this is a much better example of the efficient markets hypothesis than share markets or asset prices!). However, not all bookies offer the same odds, since the bookies try to balance the financial risk that they face from any particular outcome. So, a bookie that receives a lot of bets on the underdog will adjust the underdog's odds downwards (and the favourite's odds upwards), in order to maintain some balance.
Is it possible to exploit those differences in different bookmakers' odds on the same event in order to make money? True arbitrage opportunities are rare, as that would require one bookie to have one outcome favoured, while at the same time another bookies has a different outcome favoured. However, it may nevertheless be possible to take advantage of the difference in odds. The method is explained in this 2017 paper by Lisandro Kaunitz (University of Tokyo), Shenjun Zhong (Monash University), and Javier Kreiner (CargoX). As they explain:
Our betting system differed from previous betting strategies in that, instead of trying to build a model to compete with bookmakers’ forecasting expertise, we used their publicly available odds as a proxy of the true probability of a game outcome. With these proxies we searched for mispricing opportunities, i.e., games with odds offered above the estimated fair value...
The 'fair value' of a bet was based on the average odds of at least three bookies (Kaunitz et al. followed the odds of 32 different bookmakers for domestic and international football (soccer) games. Their success was remarkable:
Our strategy returned sustained profits over years of simulated betting with historical data, and months of paper trading and betting with actual money...
Specifically, the simulated betting:
...reached an accuracy of 44.4% and yielded a 3.5% return over the analysis period. For example, for an imaginary stake of $50 per bet, this corresponds to an equivalent profit of $98,865 across 56,435 bets...
The paper trading:
...obtained an accuracy of 44.4% and a return of 5.5%, earning $1,128.50 across 407 bets for the case of $50 bets...
And finally, betting with real money:
...obtained an accuracy of 47.% and a profit of $957.50 across 265 bets, equivalent to a 8.5% return...
But, just when Kaunitz et al. were probably starting to plan their semi-retirement on the Costa Azul, the bookies struck back:
Although we played according to the sports betting industry rules, a few months after we began to place bets with actual money bookmakers started to severely limit our accounts. We had some of our bets limited in the stake amount we could lay and bookmakers sometimes required “manual inspection” of our wagers before accepting them. In most cases, bookmakers denied us the opportunity to bet or suggested a value lower than our fixed bet of $50...
Kaunitz et al. conclude that the whole system is rigged. They found a way to exploit the imperfections in bookmakers' odds, but that only succeeded in drawing attention to them. The bookies only want losing players to play.
[HT; Marginal Revolution, here (for the Dilan Esper Twitter thread), and here (for the Kaunitz et al. paper)]
*****
[*] I admit that I am not immune to this effect. Back when I was a PhD student, I had an extremely successful run betting on NHL games, making hundreds of dollars in winnings over a few months. I thought I had a good system. However, the betting strategy didn't transfer to NBA games, where I lost all of my NHL winnings and more in the space of a few weeks. I haven't gambled on sports since.
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